Here, data are are plotted for two multiday stations, N2S4 and N3S6
library(tidyverse)
library(rmarkdown)
library(knitr)
library(readxl)
library(data.table)
library(scales)
library(zoo)
library(oce)
library(patchwork)
#rmarkdown tables
library(stargazer)
library(pander)
#stat tests
library(lmtest)
library(lmodel2)
library(rstatix)
library(ggpubr)
#for odv type plots
library(lubridate)
library(reshape2)
library(MBA)
library(mgcv)
custom_theme <- function() {
theme_test(base_size = 30) %+replace%
theme(legend.position = "right",
legend.spacing.x = unit(0.5,"cm"),
legend.title = element_text(size = 14),
legend.text = element_text(size = 14),
legend.background = element_rect(fill = "transparent",colour = NA),
legend.key = element_rect(fill = "transparent",colour = NA),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA))
}
custom.colors <- c("AT39" = "#377EB8", "AT34" = "#4DAF4A", "AT38" = "#E41A1C", "AT32" = "#FF7F00", "Temperate" = "#A6CEE3", "Subpolar" = "#377EB8", "Subtropical" = "#FB9A99", "GS/Sargasso" = "#E41A1C", "Early Spring" = "#377EB8", "Late Spring" = "#4DAF4A","Early Autumn" = "#E41A1C", "Summer" = "#E41A1C", "Late Autumn" = "#FF7F00", "Gv2_2019" = "#377EB8", "WOA18_MN" = "#4DAF4A", "WOA18_AN" = "#E41A1C")
levels = c("GS/Sargasso", "Subtropical", "Temperate", "Subpolar", "AT39-6", "AT34", "AT38", "AT32","South", "North", "Early Spring", "Late Spring","Early Autumn", "Summer", "Late Autumn", "Gv2_2019", "WOA18_MN", "WOA18_AN","Nov", "Nov sd", "Dec", "Dec sd", "Jan", "Jan sd", "Feb", "Feb sd", "Mar", "Mar sd", "Apr", "Apr sd", "Cruise", "ARGO")
bar.colors <- c("100 m" = "white", "CM" = "#4DAF4A", "PAM" = "#377EB8")
odv.colors <- c("#feb483", "#d31f2a", "#ffc000", "#27ab19", "#0db5e6", "#7139fe", "#d16cfa")
data <- read_rds("~/GITHUB/naames_multiday/Output/processed_data.df")
ctd <- read_rds("~/GITHUB/naames_multiday/Input/ctd/deriv_naames_ctd.rds") %>%
rename(lat = "Latitude [degrees_north]",
z = bin_depth) %>%
mutate(bin = round(lat, 1))
subset <- ctd %>%
filter(between(z, 0, 300)) %>%
select(lat, z, beamT_perc) %>%
group_by(z) %>%
mutate(mean = mean(beamT_perc),
sd = sd(beamT_perc),
zscore = (beamT_perc - mean)/sd) %>%
ungroup() %>%
select(lat, z, zscore) %>%
mutate(zscore = round(zscore, 2)) %>%
filter(z > 0)
mba <- mba.surf(subset, no.X = 300, no.Y = 300, extend = F)
dimnames(mba$xyz.est$z) <- list(mba$xyz.est$x, mba$xyz.est$y)
mba <- melt(mba$xyz.est$z, varnames = c('lat', 'z'), value.name = 'zscore') %>%
filter(z > 0)
subset <- ctd %>%
filter(between(z, 0, 300)) %>%
select(lat, z, fl_mg_m3) %>%
group_by(z) %>%
mutate(mean = mean(fl_mg_m3),
sd = sd(fl_mg_m3),
zscore = (fl_mg_m3 - mean)/sd) %>%
ungroup() %>%
select(lat, z, zscore) %>%
mutate(zscore = round(zscore, 2)) %>%
filter(z > 0)
mba <- mba.surf(subset, no.X = 300, no.Y = 300, extend = F)
dimnames(mba$xyz.est$z) <- list(mba$xyz.est$x, mba$xyz.est$y)
mba <- melt(mba$xyz.est$z, varnames = c('lat', 'z'), value.name = 'zscore') %>%
filter(z > 0)
subset <- data %>%
rename(lat = Latitude) %>%
filter(between(z, 0, 300)) %>%
select(lat, z, ba) %>%
group_by(z) %>%
mutate(mean = mean(ba, na.rm = T),
sd = sd(ba, na.rm = T),
zscore = (ba - mean)/sd) %>%
ungroup() %>%
select(lat, z, zscore) %>%
mutate(zscore = round(zscore, 2)) %>%
filter(z > 0) %>%
drop_na(zscore)
mba <- mba.surf(subset, no.X = 300, no.Y = 300, extend = F)
dimnames(mba$xyz.est$z) <- list(mba$xyz.est$x, mba$xyz.est$y)
mba <- melt(mba$xyz.est$z, varnames = c('lat', 'z'), value.name = 'zscore') %>%
filter(z > 0)
subset <- data %>%
rename(lat = Latitude) %>%
filter(between(z, 0, 300)) %>%
select(lat, z, bcd) %>%
group_by(z) %>%
mutate(mean = mean(bcd, na.rm = T),
sd = sd(bcd, na.rm = T),
zscore = (bcd - mean)/sd) %>%
ungroup() %>%
select(lat, z, zscore) %>%
mutate(zscore = round(zscore, 2)) %>%
filter(z > 0) %>%
drop_na(zscore)
mba <- mba.surf(subset, no.X = 300, no.Y = 300, extend = F)
dimnames(mba$xyz.est$z) <- list(mba$xyz.est$x, mba$xyz.est$y)
mba <- melt(mba$xyz.est$z, varnames = c('lat', 'z'), value.name = 'zscore') %>%
filter(z > 0)